@article {152899, title = {The alteration of structural network upon transient association between proteins studied using graph theory.}, journal = {Proteins}, volume = {93}, year = {2025}, month = {2025 Jan}, pages = {217-225}, abstract = {

Proteins such as enzymes perform their function by predominant non-covalent bond interactions between transiently interacting units. There is an impact on the overall structural topology of the protein, albeit transient nature of such interactions, that enable proteins to deactivate or activate. This aspect of the alteration of the structural topology is studied by employing protein structural networks, which are node-edge representative models of protein structure, reported as a robust tool for capturing interactions between residues. Several methods have been optimized to collect meaningful, functionally relevant information by studying alteration of structural networks. In this article, different methods of comparing protein structural networks are employed, along with spectral decomposition of graphs to study the subtle impact of protein-protein interactions. A detailed analysis of the structural network of interacting partners is performed across a dataset of around 900 pairs of bound complexes and corresponding unbound protein structures. The variation in network parameters at, around, and far away from the interface are analyzed. Finally, we present interesting case studies, where an allosteric mechanism of structural impact is understood from communication-path detection methods. The results of this analysis are beneficial in understanding protein stability, for future engineering, and docking studies.

}, keywords = {Algorithms, Allosteric Regulation, Databases, Protein, Models, Molecular, Protein Binding, Protein Conformation, Protein Interaction Mapping, Protein Interaction Maps, Proteins}, issn = {1097-0134}, doi = {10.1002/prot.26606}, author = {Prabantu, Vasam Manjveekar and Tandon, Himani and Sandhya, Sankaran and Sowdhamini, Ramanathan and Srinivasan, Narayanaswamy} } @article {117965, title = {Structures of distantly-related interacting protein homologues are less divergent than non-interacting homologues.}, journal = {FEBS Open Bio}, year = {2022}, month = {2022 Sep 23}, abstract = {

Homologous proteins can display high structural variation due to evolutionary divergence at low sequence identity. This classical inverse relationship between sequence identity and structural similarity, established many years ago, has remained true between homologous proteins of known structure over time. However, a large number of heteromeric proteins also exist in the structural data bank, where the interacting subunits belong to the same fold and maintain low sequence identity between themselves. It is not clear if there is any selection pressure to deviate from the inverse sequence-structure relationship for such interacting distant homologues, in comparison to pairs of homologues which are not known to interact. We examined 12,824 fold pairs of interacting homologues of known structure, which includes both heteromers and multi-domain proteins. These were compared with monomeric proteins, resulting in 26,082 fold pairs as a dataset of non-interacting homologous systems. Interacting homologues were found to retain higher structural similarity than non-interacting homologues at diminishing sequence identity in a statistically significant manner. Interacting homologues are more similar in their 3D structures than non-interacting homologues and have a preference towards symmetric association. There appears to be a structural constraint between remote homologues due to this commitment.

}, issn = {2211-5463}, doi = {10.1002/2211-5463.13492}, author = {Naveenkumar, Nagarajan and Prabantu, Vasam Manjveekar and Vishwanath, Sneha and Sowdhamini, Ramanathan and Srinivasan, Narayanaswamy} } @article {91672, title = {Influence of Disease-Causing Mutations on Protein Structural Networks.}, journal = {Front Mol Biosci}, volume = {7}, year = {2021}, month = {2020}, pages = {620554}, abstract = {

The interactions between residues in a protein tertiary structure can be studied effectively using the approach of protein structure network (PSN). A PSN is a node-edge representation of the structure with nodes representing residues and interactions between residues represented by edges. In this study, we have employed weighted PSNs to understand the influence of disease-causing mutations on proteins of known 3D structures. We have used manually curated information on disease mutations from UniProtKB/Swiss-Prot and their corresponding protein structures of wildtype and disease variant from the protein data bank. The PSNs of the wildtype and disease-causing mutant are compared to analyse variation of global and local dissimilarity in the overall network and at specific sites. We study how a mutation at a given site can affect the structural network at a distant site which may be involved in the function of the protein. We have discussed specific examples of the disease cases where the protein structure undergoes limited structural divergence in their backbone but have large dissimilarity in their all atom networks and vice versa, wherein large conformational alterations are observed while retaining overall network. We analyse the effect of variation of network parameters that characterize alteration of function or stability.

}, issn = {2296-889X}, doi = {10.3389/fmolb.2020.620554}, author = {Prabantu, Vasam Manjveekar and Naveenkumar, Nagarajan and Srinivasan, Narayanaswamy} }